2021 IEEE International Conference on Digital Society and Intelligent Systems (IEEE-DSInS 2021)
Dr. Quan Bai

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Dr. Quan Bai

School of ICT, University of Tasmania, Australia


Biography: Dr. Quan Bai is an associate professor and the leader of the AI Research Group at the School of ICT, University of Tasmania (UTAS), Australia. His research mainly focuses on multi-agent coordination, trust mining and agent-based modelling for complex systems. He has over 110 research publications and attracted more than $2,000,000 research grants. He has involved in the organisation of a number of international conferences, including AAMAS, PRIMA, PRICAI and AJCAI.


Research Area: Multi-agent systems, agent-based modelling, knowledge representation and discovery, data mining, machine learning


Speech title: Agent-based Influence Propagation Modelling: Methods and Applications


Abstract: With the increasing popularity of online social networks, online information sharing turns out to be pervasive. A variety of innovations simultaneously propagates through online social networks, including both positive and negative information. Influence modelling and control are complex, but critical for many applications. For example, the spread of any undesirable influence potentially breeds threat of rumours and misinformation, which may arouse extensive attention from society. In this talk, I am going to introduce the use of agent-based modelling in influence propagation analysis, and some applications of these methods.